Practices in radiation oncology quality assurance rounds: A scoping review protocol
Bibliographic record
Abstract
In radiation oncology (RO), quality assurance (QA) rounds are conducted regularly. During these rounds, charts are reviewed with the goal of ensuring standards of care are met, strengthening communication on an allied health team, and monitoring for any potential deficits or areas of improvement. Barriers to effective QA rounds can include time and scheduling commitments, lengthy discussion periods, and lack of equal and consistent contributions from all allied health members present. Recent studies have examined the implementation of specific practices into QA rounds such as random insertion of realistic errors and Group Consensus Peer Review (Talcott et al. 2020; Duggar et al., 2018). This scoping review aims to (1) provide practicing radiation oncologists a general landscape of current published practices in QA rounds, and (2) inform an improvement study targeting gastrointestinal-focused (GI) RO at the University of Calgary.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".